Super resolution and color motion artifact correction in a pulsed color imaging system

ABSTRACT

The disclosure extends to methods, systems, and computer program products for producing an image in light deficient environments and associated structures, methods and features. The features of the systems and methods described herein may include providing improved resolution and color reproduction.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of Ser. No. 15/583,893, filed May 1,2017 (now U.S. Pat. No. 10,205,877, issued Feb. 12, 2019), and which isa continuation of U.S. application Ser. No. 14/214,311, filed Mar. 14,2014 (now U.S. Pat. No. 9,641,815, issued May 2, 2017) and which claimsthe benefit of (1) U.S. Provisional Application No. 61/791,473, filedMar. 15, 2013; (2) U.S. Provisional Application No. 61/790,487, filedMar. 15, 2013; and (3) U.S. Provisional Application No. 61/790,804,filed Mar. 15, 2013; all of which are incorporated herein by referencein their entireties, including but not limited to those portions thatspecifically appear hereinafter, the incorporation by reference beingmade with the following exception: In the event that any portion of anyof the above-referenced applications are inconsistent with thisapplication, this application supersedes said above-referencedprovisional applications.

STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT

Not Applicable.

BACKGROUND

Advances in technology have provided advances in imaging capabilitiesfor medical use. One area that has enjoyed some of the most beneficialadvances is that of endoscopic surgical procedures because of theadvances in the components that make up an endoscope.

The disclosure relates generally to electromagnetic sensing and sensors.The disclosure also relates generally to increasing the resolution andcolor accuracy of a video stream. The features and advantages of thedisclosure will be set forth in the description which follows, and inpart will be apparent from the description, or may be learned by thepractice of the disclosure without undue experimentation. The featuresand advantages of the disclosure may be realized and obtained by meansof the instruments and combinations particularly pointed out in theappended claims.

BRIEF DESCRIPTION OF THE DRAWINGS

Non-limiting and non-exhaustive implementations of the disclosure aredescribed with reference to the following figures, wherein likereference numerals refer to like parts throughout the various viewsunless otherwise specified. Advantages of the disclosure will becomebetter understood with regard to the following description andaccompanying drawings where:

FIG. 1 illustrates a flow chart of a method and system for producing animage in a light deficient environment made in accordance with theprinciples and teachings of the disclosure;

FIG. 2 is an illustration of a schematic of a pixel array configured inan x and y plane;

FIG. 3 is an illustration of a schematic of a pixel array configured inan x and y plane in accordance with the principles and teachings of thedisclosure;

FIG. 4 is a graphical representation of an imaged object's motionthrough time in accordance with the principles and teachings of thedisclosure;

FIG. 5 illustrates a schematic of supporting and enabling hardware inaccordance with the principles and teachings of the disclosure;

FIGS. 6A and 6B illustrate a perspective view and a side view,respectively, of an implementation of a monolithic sensor having aplurality of pixel arrays for producing a three dimensional image inaccordance with the teachings and principles of the disclosure;

FIGS. 7A and 7B illustrate a perspective view and a side view,respectively, of an implementation of an imaging sensor built on aplurality of substrates, wherein a plurality of pixel columns formingthe pixel array are located on the first substrate and a plurality ofcircuit columns are located on a second substrate and showing anelectrical connection and communication between one column of pixels toits associated or corresponding column of circuitry; and

FIGS. 8A and 8B illustrate a perspective view and a side view,respectively, of an implementation of an imaging sensor having aplurality of pixel arrays for producing a three dimensional image,wherein the plurality of pixel arrays and the image sensor are built ona plurality of substrates.

DETAILED DESCRIPTION

The disclosure extends to methods, systems, and computer based productsfor digital imaging that may be primarily suited to medicalapplications. In the following description of the disclosure, referenceis made to the accompanying drawings, which form a part hereof, and inwhich is shown by way of illustration specific implementations in whichthe disclosure may be practiced. It is understood that otherimplementations may be utilized and structural changes may be madewithout departing from the scope of the disclosure.

For any digital imaging system, the final quality of video dependsfundamentally on the engineering details of the front-end imageelectronic capture process. Broadly speaking, perceived image quality isdependent on the following properties:

Signal to noise ratio (SNR)

Dynamic range (DR)

Spatial resolution

Perception of visible unnatural artifacts

Perception of spatial distortion

Color fidelity and appeal

In general, manufacturers of cameras for many common purposes facecontinuous pressure toward greater miniaturization and lower cost. Bothfactors may have a detrimental effect however, on their ability todeliver high quality images.

More expensive cameras often use three monochrome sensors, preciselycoupled to an elaborate arrangement of prisms and filters, since thatprovides for the best spatial resolution and color separation. Colorcameras based on a single sensor generally have individual pixel-sizedcolor filters fabricated onto the sensor in a mosaic arrangement. Themost popular mosaic is the Bayer pattern, which exploits the fact thatspatial resolution is more important for green data than for red orblue. While much cheaper to fabricate, Bayer based cameras cannotachieve the image quality realized by three-sensor solutions because ofthe spacing of the pattern. Sophisticated interpolation (demosaic)algorithms, such as that proposed by Malvar, He and Cutlar at MicrosoftResearch, help to reduce the resolution loss, but it can never be fullyrecovered. Another undesirable side-effect comes in the form ofartifacts introduced by the color segmentation pattern, which areespecially egregious around black and white edges. This can be addressedby lowering the optical MTF, but that may further degrade the finalcamera resolution.

If pixel count is a valued trait, that may necessitate smaller pixels inorder to make a marketable product. Smaller pixels naturally have lowersignal capacity which may reduce the dynamic range. Lower signalcapacity also means the maximum possible signal to noise ratio isreduced, since photon shot noise scales as the square root of the signalcharge. Lowering the pixel area also reduces the sensitivity, not onlyin proportion with the capture area, but quite likely at an even greaterrate than that. This is because it becomes harder to direct photons intothe light sensitive structure and thus to maintain quantum efficiency.Loss of sensitivity may be compensated by lowering the F-number,however, that may reduce the depth of focus (which impacts theresolution), and may lead to greater spatial distortion. Smaller pixelsare also harder to manufacture consistently, which may result in greaterdefect rates, etc.

Rather than making the pixels smaller, it is thus desirable to seekother ways to bolster the resolution. This disclosure concerns anapproach in which a monochrome sensor is employed. The color informationis produced by illuminating different frames with alternating singlewavelengths (i.e. red, green and blue) or combinations thereof. Thisallows the full pixel count to be exploited and Bayer artifacts to beavoided, as in three-sensor cameras. One issue with the frame-wise colorswitching arises from motion occurring within the scene, from frame toframe. Since different frames supply different color components,unnatural, colored effects may be visible, particularly in the vicinityof significant edges. Implementations may involve a full custom sensorcapable of captured frame rates as high as e.g. 240 fps. Having accessto such high rates allows for high progressive video rates (e.g. 60 P orhigher), post-color reconstruction. While the high capture rate limitsthe impact of color motion artifacts, they may still be visibledepending on the incident angular rate of motion of the scene, or of anyobject within it, relative to the sensor.

An implementation may employ an approach to colored frame pulsing inwhich the red, green and blue monochromatic sources are pulsed incombination. For every second frame, their relative energies are set inproportion to the standard luminance (Y) coefficients, so as to providedirect luminance information. On the alternate frames, the chrominance(Cb and Cr) information is provided by making a linear sum of thestandard luminance and chrominance coefficients in order to bring thecorresponding individual pulse energies to zero or positive values. Thechrominance frames themselves alternate between Cb and Cr. This isreferred to herein as the Y-Cb-Y-Cr sequence. This approach offers anadvantage in terms of perceived resolution, compared with pure red,green and blue (R-G-B-G) pulsing, since all of the Y information perresulting output frame is derived from a single captured frame. WithR-G-B-G pulsing, data is combined from three adjacent frames to providethe luminance. Therefore any motion will impact the resultant imagesharpness.

A system designed for small diameter endoscopes with the image sensorplaced at the distal end may be realized, which may preserve HDresolution, high inherent dynamic range and high sensitivity at the sametime. The basis of this is a specially designed monochrome sensor whichhas fewer pixels than, e.g., a 1280×720 Bayer sensor, but which hassuperior spatial resolution by virtue of being monochrome. Maintaining arelatively large pixel at the expense of pixel count has multipleadvantages for image quality, as discussed earlier.

In this disclosure, a method is described to further enhance theperceived resolution by applying the principal of super-resolution (SR)and to correct for the color artifacts resulting from the frame-wisemodulation of color (CMAC), by making use of the motion information thatis extracted by the SR algorithm.

Before the structure, systems and methods for producing an image in alight deficient environment are disclosed and described, it is to beunderstood that this disclosure is not limited to the particularstructures, configurations, process steps, and materials disclosedherein as such structures, configurations, process steps, and materialsmay vary somewhat. It is also to be understood that the terminologyemployed herein is used for the purpose of describing particularembodiments only and is not intended to be limiting since the scope ofthe disclosure will be limited only by the appended claims andequivalents thereof.

In describing and claiming the subject matter of the disclosure, thefollowing terminology will be used in accordance with the definitionsset out below.

It must be noted that, as used in this specification and the appendedclaims, the singular forms “a,” “an,” and “the” include plural referentsunless the context clearly dictates otherwise.

As used herein, the terms “comprising,” “including,” “containing,”“characterized by,” and grammatical equivalents thereof are inclusive oropen-ended terms that do not exclude additional, unrecited elements ormethod steps.

As used herein, the phrase “consisting of” and grammatical equivalentsthereof exclude any element or step not specified in the claim.

As used herein, the phrase “consisting essentially of” and grammaticalequivalents thereof limit the scope of a claim to the specifiedmaterials or steps and those that do not materially affect the basic andnovel characteristic or characteristics of the claimed disclosure.

As used herein, the term “proximal” shall refer broadly to the conceptof a portion nearest an origin.

As used herein, the term “distal” shall generally refer to the oppositeof proximal, and thus to the concept of a portion farther from anorigin, or a furthest portion, depending upon the context.

As used herein, color sensors or multi spectrum sensors are thosesensors known to have a color filter array (CFA) thereon so as to filterthe incoming electromagnetic radiation into its separate components. Inthe visual range of the electromagnetic spectrum, such a CFA may bebuilt on a Bayer pattern or modification thereon in order to separategreen, red and blue spectrum components of the light.

In super resolution (SR), data from multiple, adjacent frames arecombined to produce individual frames with higher spatial resolution.This depends upon accurate motion detection within local regions of thescene. Since the luminance plane is the most critical for spatialresolution, this is done for luminance frames only (or for green framesin the case of R-G-B-G light pulsing).

The systems and methods disclosed herein will be described in thecontext of the Y-Cb-Cr light pulsing scheme. However, the systems andmethods of the disclosure are not limited or restricted to thatparticular pulsing scheme and are also applicable to the R-G-B-G imagesequence scenario, with G taking the place of Y, and R and B taking theplace of Cr and Cb.

There are four types of captured frames. Thus, for example, imagine f isa continuously rotating frame index which repeatedly counts from 0 to 3during active video capture.

Then:

If (f mod 4)=0 or (f mod 4)=2 it is a Y frame, containing pure luminanceinformation.

If (f mod 4)=1, it is a ‘Cb’ frame, containing a linear sum of Y and Cbdata (Cb+Y).

If (f mod 4)=3, it is a ‘Cr’ frame, containing a linear sum of Y and Crdata (Cr+Y).

During frame reconstruction (color fusion), there may be one full colorframe (in YCbCr space) generated for each luminance frame at the input.The luminance data may be combined with the chrominance data from theframe prior to and the frame following the Y frame. Note that given thispulsing sequence, the position of the Cb frame with respect to the Yframe ping-pongs between the before and after slots for alternate Ycases, as does its complementary Cr component. Therefore, the data fromeach captured Cb or Cr (i.e., C) frame may actually be utilized in tworesultant full-color images. The minimum frame latency may be providedby performing the color fusion process during C frame capture.

FIG. 1 illustrates a flow chart of a method and system 100 for producingan image, image stream, or video in a light deficient environment madein accordance with the principles and teachings of the disclosure. Itwill be appreciated that the super resolution (SR) and color motionartifact correction (CMAC) processes 106 may take place within thecamera ISP on raw, captured sensor data 102, right after all the digitalsensor correction processes 104 and prior to fusion into linear RGB orYCbCr space color images. FIG. 1 illustrates placement of superresolution (SR) and color motion artifact correction (CMAC) within acamera ISP chain designed for frame-wise color modulation with Y-Cb-Y-Crsequencing.

Two frame FIFOs are constructed, one for Y frames 110 in arrival order,the other for Cb plus Cr frames 108. The number of frames to use for thesuper resolution (SR) process is an optional variable. The Y FIFO depthwould normally be odd in an actual embodiment, and its size would bedetermined by the available processing, memory or memory-bandwidth, orby motion detection precision or acceptable latency considerations. CMACcan in principle be performed with the minimum FIFO depth of 3 framesfor Y and 2 for C. For the super resolution (SR) aspect, the use of 5‘Y’ frames may result in better resolution. On Y frames, the currentobject frame may be the central frame in the Y FIFO. On chrominanceframes, the two C frames that flank the central Y frame may be adjustedin order to line up their motion to the central Y frame.

The motion detection method described here may be based upon the blockmatching approach which provides x and y motion vectors for small,independent blocks of pixels of configurable dimensions. There are othermotion detection algorithms that could also be used in principle. Blockmatching offers advantages for simplicity of implementation,particularly for real time processing in hardware. A 2-stage matchprocess is described which provides for a super resolved frame withdouble the pixel count in x and y. Further stages could be added toincrease the pixel count further, however many more buffered frames andcomputation would be required to make it worthwhile.

In addition to the raw, buffered, Y object frame sitting in the middleof the Y FIFO (referred to as RY), three ×2 up-scaled versions of it maybe created. The first may be up-scaled using bilinear interpolation(referred to as buffer BL), the second using bicubic interpolation(buffer BC) and the third with no interpolation, just zeros where theempty pixels are (called NI). BL may be used in the block matchingmethod, NI forms the baseline for the super-resolved frame and BC is thefallback pixel source for unfilled pixels within the super-resolvedframe.

Referring to FIG. 2, there is illustrated a schematic of a pixel array201 configured in an x and y plane. For each Y frame in the buffer,except for RY, the array may be segmented into square blocks 206 of somedimension, (e.g., 4×4). Each block 206 of pixels 202 may be shiftedaround, one pixel at a time, in both x and y, within some defined rangeof shifts in both + and − directions (e.g., +/−3 pixels). For eachlocation it may be compared to the equivalent block 208 of pixels 204sitting in that location with the object frame, RY. The x and y shiftsencountered for the best match position become the recorded Cartesianmotion co-ordinates for all pixels within the block. There may bevarious ways to make the comparison and a relatively convenient metric.One implementation may be to take the modulus of the pixel differences,(i.e., between the stationary pixel 204 in RY and the correspondingpixel in the block 206 under study), summed over all pixels in theblock. The best match may be taken as the minimum of this value. It canalso be recorded for each block as a matching quality metric, which maybe used to arbitrate between competing pixels during the superresolution (SR) process. In an implementation, the minimum sum ofsquared differences may be used as the matching metric, for example.

Referring now to FIG. 3, at this stage, each pixel 302 within non-RY,Y-frames, has a motion estimate that is quantized at the capturedresolution. This may not provide a feature or use for super resolution(SR), but it can nevertheless be used for the CMAC, if no superresolution (SR) is desired. If ×2 super resolution is sought, the nextstage involves, for block of pixels 306 within the non-RY frames 302,comparing to the BL buffer instead of the RY buffer. Starting from thebest shifted position (according to the recorded motion vectors), shiftsare performed by + and −1 half-pixel, giving a total of 9 possiblepositions as illustrated best in FIG. 3. A half-pixel in the Y frameunder study is one whole pixel with respect to BL. Of those 9 possiblepixel positions, the best match is again determined and the recordedmotion vector is adjusted accordingly. If the motion vector at thisstage has a half integer component (with ˜75% probability), then it hasthe potential to enhance the final resolution.

Motion vectors for the two Y frames flanking RY, may be saved for theCMAC process, which occurs during the C frames.

The super resolution (SR) process itself may involve combining data frommultiple Y frames into a central super-resolved frame, which isstationary with respect to the RY buffer. For each of the non-central Ybuffers, a ×2 up-scaled version may be produced, in which the individualblocks have been shifted according to their (x,y) motion vectors. Anypixels at the ×2 resolution that are not filled after shifting are leftblank.

The basis of the super-resolved frame is the NI buffer, which is theup-scaled version of RY with no interpolation. Three out of every fourpixels in NI may be initially blank, and the primary objective is tofill the pixels with data from the up-scaled & shifted Y buffers. Oneapproach may be to scan through the pixels looking for the first matchfor each empty pixel. At the end, any pixels that are still blank may befilled in from the BC buffer, which is the bicubic interpolated versionof the central Y frame. Another approach to filling blank pixels may beto assess all possible candidates and choose the best one, based on someparameter that has been logged as a motion estimate quality metric. Anexample of such a metric may be the minimum sum of absolute differencesfor the originating block of pixels, or some derivative thereof. Thisrequires at least one additional frame buffer per Y frame.Alternatively, all candidates can be combined in some way, e.g., as anaverage, which can be, e.g., weighted according to a quality parameter.In this case, even the non-zero pixels in NI can be substituted as well.The benefit may be that in addition to enhancing the resolution, the netsignal to noise ratio is improved. Candidates with notably poor qualityvalues can also be rejected altogether.

FIG. 4 illustrates the issue of significant motion from frame to framewith frame-wise color modulation. In the figure, the ball 402 isillustrated as moving on a trajectory across the scene during capture,resulting in different positions for the Y, Cb and Cr components. Thecolor motion artifact correction may utilize the relative motionestimate for adjacent Y frames, to predict the motion that occurred forthe intermediate C frames relative to the Y frame, to which they becomeassociated during color fusion. One implementation may be to take themotion vectors and divide them by 2. In this implementation, there is anassumption that any motion that has occurred from Y frame to Y frame islinear. In an implementation, if motion estimation is available for 3 ormore Y frames in addition to the object frame (RY), then bicubicinterpolation may be employed for a more precise interpolation.

The pixel shifting can take place either at the original or the doubledresolution, following a bicubic upscale. Either way, after shiftingthere are many void locations with various random shapes and sizes to befilled in.

The application of the motion information is a little different for CMACcompared with super resolution (SR). Super resolution (SR) has thebicubic up-scaled version of RY as its default, so the worst case isthat a pixel void is filled by interpolation using its sixteen closestneighbors in the correct motion frame. For CMAC there may be nopredicting the distance of the nearest filled neighbors, all is known isthat it is limited to the original block search distance divided by two(in the case of linear interpolation). Some means of interpolation isthus required to fill in the holes. One implementation to do this is foreach missing pixel, find the distance to the closest filled pixel in +x,−x, +y and −y, then fill with an average level that has been weightedaccording to the reciprocal of each distance.

It should be noted that as used herein the term “light” is both aparticle and a wavelength, and is intended to denote electromagneticradiation that is detectable by a pixel array, and may be includewavelengths from the visible and non-visible spectrums ofelectromagnetic radiation. The term “partition” is used herein to mean apredetermined range of wavelengths of the electromagnetic spectrum thatis less than the entire spectrum, or in other words, wavelengths thatmake up some portion of the electromagnetic spectrum. An emitter may bea light source that is controllable as to the portion of theelectromagnetic spectrum that is emitted, the intensity of theemissions, or the duration of the emission, or all three. An emitter mayemit light in any dithered, diffused, or columnated emission and may becontrolled digitally or through analog methods or systems.

A pixel array of an image sensor may be paired with an emitterelectronically, such that they are synced during operation for bothreceiving the emissions and for the adjustments made within the system.An emitter may be tuned to emit electromagnetic radiation, which may bepulsed in order to illuminate an object. It will be appreciated that theemitter may be in the form of a laser, which may be pulsed in order toilluminate an object. The emitter may pulse at an interval thatcorresponds to the operation and functionality of a pixel array. Theemitter may pulse light in a plurality of electromagnetic partitions,such that the pixel array receives electromagnetic energy and produces adata set that corresponds (in time) with each specific electromagneticpartition.

A system may comprise a monochromatic pixel array (black and white),which is simply sensitive to electromagnetic radiation of anywavelength. The light emitter illustrated in the figure may be a laseremitter that is capable of emitting a green electromagnetic partition, ablue electromagnetic partition, and a red electromagnetic partition inany desired sequence. It will be appreciated that other light emittersmay be used without departing from the scope of the disclosure, such asdigital or analog based emitters.

During operation, the data created by the monochromatic sensor for anyindividual pulse may be assigned a specific color partition, wherein theassignment may be based on the timing of the pulsed color partition fromthe emitter. Even though the pixels are not color dedicated they can beassigned a color for any given data set based on timing. In oneembodiment, three data sets representing RED, GREEN and BLUE pulses maythen be combined to form a single image frame. It will be appreciatedthat the disclosure is not limited to any particular color combinationor any particular electromagnetic partition, and that any colorcombination or any electromagnetic partition may be used in place ofRED, GREEN and BLUE, such as Cyan, Magenta and Yellow, Ultraviolet,infra-red, or any other color combination, including all visible andnon-visible wavelengths, without departing from the scope of thedisclosure. The object to be imaged contains a red portion, greenportion and a blue portion. As illustrated in the figure, the reflectedlight from the electromagnetic pulses only contains the data for theportion of the object having the specific color that corresponds to thepulsed color partition. Those separate color (or color interval) datasets can then be used to reconstruct the image by combining the datasets.

Implementations of the disclosure may comprise or utilize a specialpurpose or general-purpose computer including computer hardware, suchas, for example, one or more processors and system memory, as discussedin greater detail below. Implementations within the scope of thedisclosure may also include physical and other computer-readable mediafor carrying or storing computer-executable instructions and/or datastructures. Such computer-readable media can be any available media thatcan be accessed by a general purpose or special purpose computer system.Computer-readable media that store computer-executable instructions arecomputer storage media (devices). Computer-readable media that carrycomputer-executable instructions are transmission media. Thus, by way ofexample, and not limitation, implementations of the disclosure cancomprise at least two distinctly different kinds of computer-readablemedia: computer storage media (devices) and transmission media.

Computer storage media (devices) includes RAM, ROM, EEPROM, CD-ROM,solid state drives (“SSDs”) (e.g., based on RAM), Flash memory,phase-change memory (“PCM”), other types of memory, other optical diskstorage, magnetic disk storage or other magnetic storage devices, or anyother medium which can be used to store desired program code means inthe form of computer-executable instructions or data structures andwhich can be accessed by a general purpose or special purpose computer.

A “network” is defined as one or more data links that enable thetransport of electronic data between computer systems and/or modulesand/or other electronic devices. In an implementation, a sensor andcamera control unit may be networked in order to communicate with eachother, and other components, connected over the network to which theyare connected. When information is transferred or provided over anetwork or another communications connection (either hardwired,wireless, or a combination of hardwired or wireless) to a computer, thecomputer properly views the connection as a transmission medium.Transmissions media can include a network and/or data links which can beused to carry desired program code means in the form ofcomputer-executable instructions or data structures and which can beaccessed by a general purpose or special purpose computer. Combinationsof the above should also be included within the scope ofcomputer-readable media.

Further, upon reaching various computer system components, program codemeans in the form of computer-executable instructions or data structuresthat can be transferred automatically from transmission media tocomputer storage media (devices) (or vice versa). For example,computer-executable instructions or data structures received over anetwork or data link can be buffered in RAM within a network interfacemodule (e.g., a “NIC”), and then eventually transferred to computersystem RAM and/or to less volatile computer storage media (devices) at acomputer system. RAM can also include solid state drives (SSDs or PCIxbased real time memory tiered Storage, such as FusionIO). Thus, itshould be understood that computer storage media (devices) can beincluded in computer system components that also (or even primarily)utilize transmission media.

Computer-executable instructions comprise, for example, instructions anddata which, when executed at a processor, cause a general purposecomputer, special purpose computer, or special purpose processing deviceto perform a certain function or group of functions. The computerexecutable instructions may be, for example, binaries, intermediateformat instructions such as assembly language, or even source code.Although the subject matter has been described in language specific tostructural features and/or methodological acts, it is to be understoodthat the subject matter defined in the appended claims is notnecessarily limited to the described features or acts described above.Rather, the described features and acts are disclosed as example formsof implementing the claims.

Those skilled in the art will appreciate that the disclosure may bepracticed in network computing environments with many types of computersystem configurations, including, personal computers, desktop computers,laptop computers, message processors, control units, camera controlunits, hand-held devices, hand pieces, multi-processor systems,microprocessor-based or programmable consumer electronics, network PCs,minicomputers, mainframe computers, mobile telephones, PDAs, tablets,pagers, routers, switches, various storage devices, and the like. Itshould be noted that any of the above mentioned computing devices may beprovided by or located within a brick and mortar location. Thedisclosure may also be practiced in distributed system environmentswhere local and remote computer systems, which are linked (either byhardwired data links, wireless data links, or by a combination ofhardwired and wireless data links) through a network, both performtasks. In a distributed system environment, program modules may belocated in both local and remote memory storage devices.

Further, where appropriate, functions described herein can be performedin one or more of: hardware, software, firmware, digital components, oranalog components. For example, one or more application specificintegrated circuits (ASICs) or field programmable gate arrays can beprogrammed to carry out one or more of the systems and proceduresdescribed herein. Certain terms are used throughout the followingdescription and claims to refer to particular system components. As oneskilled in the art will appreciate, components may be referred to bydifferent names. This document does not intend to distinguish betweencomponents that differ in name, but not function.

FIG. 5 is a block diagram illustrating an example computing device 500.

Computing device 500 may be used to perform various procedures, such asthose discussed herein. Computing device 500 can function as a server, aclient, or any other computing entity. Computing device can performvarious monitoring functions as discussed herein, and can execute one ormore application programs, such as the application programs describedherein. Computing device 500 can be any of a wide variety of computingdevices, such as a desktop computer, a notebook computer, a servercomputer, a handheld computer, camera control unit, tablet computer andthe like.

Computing device 500 includes one or more processor(s) 502, one or morememory device(s) 504, one or more interface(s) 506, one or more massstorage device(s) 508, one or more Input/Output (I/O) device(s) 510, anda display device 530 all of which are coupled to a bus 512. Processor(s)502 include one or more processors or controllers that executeinstructions stored in memory device(s) 504 and/or mass storagedevice(s) 508. Processor(s) 502 may also include various types ofcomputer-readable media, such as cache memory.

Memory device(s) 504 include various computer-readable media, such asvolatile memory (e.g., random access memory (RAM) 514) and/ornonvolatile memory (e.g., read-only memory (ROM) 516). Memory device(s)504 may also include rewritable ROM, such as Flash memory.

Mass storage device(s) 508 include various computer readable media, suchas magnetic tapes, magnetic disks, optical disks, solid-state memory(e.g., Flash memory), and so forth. As shown in FIG. 5, a particularmass storage device is a hard disk drive 524. Various drives may also beincluded in mass storage device(s) 508 to enable reading from and/orwriting to the various computer readable media. Mass storage device(s)508 include removable media 526 and/or non-removable media.

I/O device(s) 510 include various devices that allow data and/or otherinformation to be input to or retrieved from computing device 500.Example I/O device(s) 510 include digital imaging devices,electromagnetic sensors and emitters, cursor control devices, keyboards,keypads, microphones, monitors or other display devices, speakers,printers, network interface cards, modems, lenses, CCDs or other imagecapture devices, and the like.

Display device 530 includes any type of device capable of displayinginformation to one or more users of computing device 500. Examples ofdisplay device 530 include a monitor, display terminal, video projectiondevice, and the like.

Interface(s) 106 include various interfaces that allow computing device500 to interact with other systems, devices, or computing environments.Example interface(s) 506 may include any number of different networkinterfaces 520, such as interfaces to local area networks (LANs), widearea networks (WANs), wireless networks, and the Internet. Otherinterface(s) include user interface 518 and peripheral device interface522. The interface(s) 506 may also include one or more user interfaceelements 518. The interface(s) 506 may also include one or moreperipheral interfaces such as interfaces for printers, pointing devices(mice, track pad, etc.), keyboards, and the like.

Bus 512 allows processor(s) 502, memory device(s) 504, interface(s) 506,mass storage device(s) 508, and I/O device(s) 510 to communicate withone another, as well as other devices or components coupled to bus 512.Bus 512 represents one or more of several types of bus structures, suchas a system bus, PCI bus, IEEE 1394 bus, USB bus, and so forth.

For purposes of illustration, programs and other executable programcomponents are shown herein as discrete blocks, although it isunderstood that such programs and components may reside at various timesin different storage components of computing device 500, and areexecuted by processor(s) 502. Alternatively, the systems and proceduresdescribed herein can be implemented in hardware, or a combination ofhardware, software, and/or firmware. For example, one or moreapplication specific integrated circuits (ASICs) can be programmed tocarry out one or more of the systems and procedures described herein.

Referring now to FIGS. 6A and 6B, the figures illustrate a perspectiveview and a side view, respectively, of an implementation of a monolithicsensor 600 having a plurality of pixel arrays for producing a threedimensional image in accordance with the teachings and principles of thedisclosure. Such an implementation may be desirable for threedimensional image capture, wherein the two pixel arrays 602 and 604 maybe offset during use. In another implementation, a first pixel array 602and a second pixel array 604 may be dedicated to receiving apredetermined range of wave lengths of electromagnetic radiation,wherein the first pixel array 602 is dedicated to a different range ofwave length electromagnetic radiation than the second pixel array 604.

FIGS. 7A and 7B illustrate a perspective view and a side view,respectively, of an implementation of an imaging sensor 700 built on aplurality of substrates. As illustrated, a plurality of pixel columns704 forming the pixel array are located on the first substrate 702 and aplurality of circuit columns 708 are located on a second substrate 706.Also illustrated in the figure are the electrical connection andcommunication between one column of pixels to its associated orcorresponding column of circuitry. In one implementation, an imagesensor, which might otherwise be manufactured with its pixel array andsupporting circuitry on a single, monolithic substrate/chip, may havethe pixel array separated from all or a majority of the supportingcircuitry. The disclosure may use at least two substrates/chips, whichwill be stacked together using three-dimensional stacking technology.The first 702 of the two substrates/chips may be processed using animage CMOS process. The first substrate/chip 702 may be comprised eitherof a pixel array exclusively or a pixel array surrounded by limitedcircuitry. The second or subsequent substrate/chip 706 may be processedusing any process, and does not have to be from an image CMOS process.The second substrate/chip 706 may be, but is not limited to, a highlydense digital process in order to integrate a variety and number offunctions in a very limited space or area on the substrate/chip, or amixed-mode or analog process in order to integrate for example preciseanalog functions, or a RF process in order to implement wirelesscapability, or MEMS (Micro-Electro-Mechanical Systems) in order tointegrate MEMS devices. The image CMOS substrate/chip 702 may be stackedwith the second or subsequent substrate/chip 706 using anythree-dimensional technique. The second substrate/chip 706 may supportmost, or a majority, of the circuitry that would have otherwise beenimplemented in the first image CMOS chip 702 (if implemented on amonolithic substrate/chip) as peripheral circuits and therefore haveincreased the overall system area while keeping the pixel array sizeconstant and optimized to the fullest extent possible. The electricalconnection between the two substrates/chips may be done throughinterconnects 703 and 705, which may be wirebonds, bump and/or TSV(Through Silicon Via).

FIGS. 8A and 8B illustrate a perspective view and a side view,respectively, of an implementation of an imaging sensor 800 having aplurality of pixel arrays for producing a three dimensional image. Thethree dimensional image sensor may be built on a plurality of substratesand may comprise the plurality of pixel arrays and other associatedcircuitry, wherein a plurality of pixel columns 804 a forming the firstpixel array and a plurality of pixel columns 804 b forming a secondpixel array are located on respective substrates 802 a and 802 b,respectively, and a plurality of circuit columns 808 a and 808 b arelocated on a separate substrate 806. Also illustrated are the electricalconnections and communications between columns of pixels to associatedor corresponding column of circuitry.

It will be appreciated that the teachings and principles of thedisclosure may be used in a reusable device platform, a limited usedevice platform, a re-posable use device platform, or asingle-use/disposable device platform without departing from the scopeof the disclosure. It will be appreciated that in a re-usable deviceplatform an end-user is responsible for cleaning and sterilization ofthe device. In a limited use device platform the device can be used forsome specified amount of times before becoming inoperable. Typical newdevice is delivered sterile with additional uses requiring the end-userto clean and sterilize before additional uses. In a re-posable usedevice platform a third-party may reprocess the device (e.g., cleans,packages and sterilizes) a single-use device for additional uses at alower cost than a new unit. In a single-use/disposable device platform adevice is provided sterile to the operating room and used only oncebefore being disposed of.

Additionally, the teachings and principles of the disclosure may includeany and all wavelengths of electromagnetic energy, including the visibleand non-visible spectrums, such as infrared (IR), ultraviolet (UV), andX-ray.

It will be appreciated that various features disclosed herein providesignificant advantages and advancements in the art. The followingembodiments are exemplary of some of those features.

In the foregoing Detailed Description of the Disclosure, variousfeatures of the disclosure are grouped together in a single embodimentfor the purpose of streamlining the disclosure. This method ofdisclosure is not to be interpreted as reflecting an intention that theclaimed disclosure requires more features than are expressly recited ineach claim. Rather, inventive aspects lie in less than all features of asingle foregoing disclosed embodiment.

It is to be understood that the above-described arrangements are onlyillustrative of the application of the principles of the disclosure.Numerous modifications and alternative arrangements may be devised bythose skilled in the art without departing from the spirit and scope ofthe disclosure and the appended claims are intended to cover suchmodifications and arrangements.

Thus, while the disclosure has been shown in the drawings and describedabove with particularity and detail, it will be apparent to those ofordinary skill in the art that numerous modifications, including, butnot limited to, variations in size, materials, shape, form, function andmanner of operation, assembly and use may be made without departing fromthe principles and concepts set forth herein.

The foregoing description has been presented for the purposes ofillustration and description. It is not intended to be exhaustive or tolimit the disclosure to the precise form disclosed. Many modificationsand variations are possible in light of the above teaching. Further, itshould be noted that any or all of the aforementioned alternateimplementations may be used in any combination desired to formadditional hybrid implementations of the disclosure.

Further, although specific implementations of the disclosure have beendescribed and illustrated, the disclosure is not to be limited to thespecific forms or arrangements of parts so described and illustrated.The scope of the disclosure is to be defined by the claims appendedhereto, any future claims submitted here and in different applications,and their equivalents.

1. A digital imaging method for use with an endo scope in ambient lightdeficient environments comprising: actuating an emitter to emit a pulseof a wavelength of electromagnetic radiation to cause illuminationwithin the light deficient environment; wherein said pulse is within afirst wavelength range that comprises a first portion of electromagneticspectrum; pulsing said emitter at a predetermined interval; sensingreflected electromagnetic radiation from said pulse with a pixel array;wherein said pixel array is actuated at a sensing interval thatcorresponds to the pulse interval of said emitter; detecting motion ofobjects being imaged; increasing resolution for the pixel array bycompensating for the detected motion; and creating a stream of images bycombining a plurality of sensed reflected electromagnetic energies intoa frame.
 2. The method of claim 1, wherein increasing resolutioncomprises: sensing luminescence of a plurality of neighboring pixels togather luminance data; bilinear interpolating the luminance data into afirst upscaled data set; bicubic interpolating the luminance data into asecond upscaled data set; creating a baseline with no interpolation ofthe luminance data into a third upscaled data set.
 3. The method ofclaim 1, wherein said sensing process comprises sensing luminance andlinear sums of luminance plus chrominance in adjacent images in a streamof images forming a video stream.
 4. The method of claim 3, furthercomprising indexing frames within the video stream with a rotating frameindex.
 5. The method of claim 4, wherein the rotating frame indexcomprises four counts.
 6. The method of claim 5, further comprisingreconstructing the video stream by combining luminance and chrominancedata from a prior indexed frame.
 7. The method of claim 5, furthercomprising reconstructing the video stream by combining luminance andchrominance data from a prior indexed frame and following indexed frame.8. The method of claim 5, further comprising reconstructing a frame forluminance and two frames for chrominance.
 9. The method of claim 5,further comprising reconstructing the video stream by combiningluminance and chrominance data from a plurality of prior indexed framesand a plurality of latter indexed frames for increased resolution andaccuracy.
 10. The method of claim 2, wherein the first upscaled data setis used for block matching.
 11. The method of claim 2, wherein thesecond upscaled data set is used for fall back pixel data.
 12. Themethod of claim 2, wherein the third upscaled data set forms thebaseline for the resolution-enhanced data set.
 13. The method of claim1, further comprising segmenting data created by the pixel array intosegments of pixels and nearest neighbors.
 14. The method of claim 13,further comprising shifting each segment of pixels in the x directionand comparing with a neighboring frame at the same resolution, in orderto determine motion of an object being imaged in the x direction. 15.The method of claim 14, further comprising shifting each segment ofpixels in the x direction in sub-pixel increments and comparing to thefirst up-scaled data set for greater precision of motion detection inthe x direction.
 16. The method of claim 14, further comprising shiftingeach segment of pixels in the y direction and comparing with aneighboring frame at the same resolution, in order to determine motionof an object being imaged in the y direction.
 17. The method of claim16, further comprising shifting each segment of pixels in the ydirection in sub-pixel increments and comparing to the first up-scaleddata set for greater precision of motion detection in the y direction.18. The method of claim 16, further comprising determining the vector ofthe motion of the object by combining the x and y motion of the of theobject being imaged.
 19. The method of claim 18, further comprisingestimating motion to combine data from multiple luminance frames into asingle, higher resolution luminance frame.
 20. The method of claim 19,wherein said process is repeated for every frame containing luminancedata in a continuous sequence. 21-48. (canceled)